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Computer-based learning: Interleaving whole and sectional representation of neuroanatomy

Authors

  • John R. Pani,

    Corresponding author
    1. Laboratory for Visual-Spatial Learning, Department of Psychological and Brain Sciences, College of Arts and Sciences, University of Louisville, Louisville, Kentucky
    • Department of Psychological and Brain Sciences, University of Louisville, 358A Life Sciences Building, Louisville, KY 40292 USA
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  • Julia H. Chariker,

    1. Laboratory for Visual-Spatial Learning, Department of Psychological and Brain Sciences, College of Arts and Sciences, University of Louisville, Louisville, Kentucky
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  • Farah Naaz

    1. Laboratory for Visual-Spatial Learning, Department of Psychological and Brain Sciences, College of Arts and Sciences, University of Louisville, Louisville, Kentucky
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Abstract

The large volume of material to be learned in biomedical disciplines requires optimizing the efficiency of instruction. In prior work with computer-based instruction of neuroanatomy, it was relatively efficient for learners to master whole anatomy and then transfer to learning sectional anatomy. It may, however, be more efficient to continuously integrate learning of whole and sectional anatomy. A study of computer-based learning of neuroanatomy was conducted to compare a basic transfer paradigm for learning whole and sectional neuroanatomy with a method in which the two forms of representation were interleaved (alternated). For all experimental groups, interactive computer programs supported an approach to instruction called adaptive exploration. Each learning trial consisted of time-limited exploration of neuroanatomy, self-timed testing, and graphical feedback. The primary result of this study was that interleaved learning of whole and sectional neuroanatomy was more efficient than the basic transfer method, without cost to long-term retention or generalization of knowledge to recognizing new images (Visible Human and MRI). Anat Sci Educ. © 2012 American Association of Anatomists.

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